Abstract
Denied preprocessing and limited to a tiny fraction of the input, what can a computer hope to do? Surprisingly much, it turns out. A blizzard of recent results in property testing, streaming, and sublinear approximation algorithms have shown that, for a large class of problems, all but a vanishing fraction of the input data is essentially unnecessary. While grounding the discussion on a few specific examples, I will review some of the basic principles at play behind this “sublinearity” phenomenon.
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© 2003 Springer-Verlag Berlin Heidelberg
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Chazelle, B. (2003). Sublinear Computing. In: Di Battista, G., Zwick, U. (eds) Algorithms - ESA 2003. ESA 2003. Lecture Notes in Computer Science, vol 2832. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39658-1_1
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DOI: https://doi.org/10.1007/978-3-540-39658-1_1
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-20064-2
Online ISBN: 978-3-540-39658-1
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